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Excitable london: Street map analysis with oregonator model

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arXiv 2018年

作者： Adamatzky, Andrew Phillips, Neil Weerasekera, Roshan Tsompanas, Michail-Antisthenis Sirakoulis, Georgios Ch. Department of Computer Science and Creative Technologies Unconventional Computing Lab Uwe Bristol United Kingdom Department of Engineering Design and Mathematics Uwe Bristol United Kingdom Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece

We explore geometry of London's streets using computational mode of an excitable chemical system, Belousov-Zhabotinsky (BZ) medium. We virtually fill in the streets with a BZ medium and study propagation of excitation waves for a range of excitability parameters, gradual transition from excitable to subexcitable to non-excitable. We demonstrate a pruning strategy adopted by the medium with decreasing excitability when wider and ballistically appropriate streets are selected. We explain mechanics of streets selection and pruning. The results of the paper will be used in future studies of studying dynamics of cities with living excitable substrates. Copyright © 2018, The Authors. All rights reserved.

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Application of Deep Learning in Fundus Image Processing for Ophthalmic Diagnosis - A Review

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arXiv 2018年

作者： Sengupta, Sourya Singh, Amitojdeep Leopold, Henry A. Gulati, Tanmay Lakshminarayanan, Vasudevan Theoretical and Experimental Epistemology Lab School of Optometry and Vision Science University of Waterloo Ontario Canada Department of System Design Engineering University of Waterloo Ontario Canada Department of Computer Science and Engineering Manipal Institute of Technology India

An overview of the applications of deep learning in ophthalmic diagnosis using retinal fundus images is presented. We also review various retinal image datasets that can be used for deep learning purposes. Applications of deep learning for segmentation of optic disk, blood vessels and retinal layer as well as detection of lesions are reviewed. Recent deep learning models for classification of diseases such as age-related macular degeneration, glaucoma, diabetic macular edema and diabetic retinopathy are also reported. Copyright © 2018, The Authors. All rights reserved.

关键词： Ophthalmology

Vision-based speaker detection using Bayesian networks

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Vision-based speaker detection using Bayesian networks

Conference on computer Vision and Pattern Recognition (CVPR)

作者： J.M. Rehg K.P. Murphy P.W. Fieguth Cambridge Research Lab Compaq Computer Corporation Cambridge MA USA Department of Computer Science University of California Berkeley CA USA Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

The development of user interfaces based on vision and speech requires the solution of a challenging statistical inference problem: The intentions and actions of multiple individuals must be inferred from noisy and ambiguous data. We argue that Bayesian network models are an attractive statistical framework for cue fusion in these applications. Bayes nets combine a natural mechanism for expressing contextual information with efficient algorithms for learning and inference. We illustrate these points through the development of a Bayes net model for detecting when a user is speaking. The model combines four simple vision sensors: face detection, skin color, skin texture, and mouth motion. We present some promising experimental results.

关键词： Bayesian methods Face detection Application software Speech Inference algorithms Skin computer networks Testing Training data computer vision

Visualizing and evaluating complexity of textual case bases

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9th European Conference on Case-Based Reasoning, ECCBR 2008

作者： Chakraborti, Sutanu Cerviño Beresi, Ulises Wiratunga, Nirmalie Massie, Stewart Lothian, Robert Khemani, Deepak Systems Research Lab. Tata Research Development and Design Centre 54B Hadapsar Industrial Estate Pune India School of Computing Robert Gordon University Aberdeen AB25 1HG United Kingdom Department of Computer Science and Engineering Indian Institute of Technology Madras Chennai-36 India

ISBN: (纸本)3540855017

This paper deals with two relatively less well studied problems in Textual CBR, namely visualizing and evaluating complexity of textual case bases. The first is useful in case base maintenance, the second in making informed choices regarding case base representation and tuning of parameters for the TCBR system, and also for explaining the behaviour of different retrieval/classification techniques over diverse case bases. We present an approach to visualize textual case bases by "stacking" similar cases and features close to each other in an image derived from the case-feature matrix. We propose a complexity measure called GAME that exploits regularities in stacked images to evaluate the alignment between problem and solution components of cases. GAME class , a counterpart of GAME in classification domains, shows a strong correspondence with accuracies reported by standard classifiers over classification tasks of varying complexity. © Springer-Verlag Berlin Heidelberg 2008.

关键词： Case based reasoning

Attention-Guided Second-Order Pooling Convolutional Networks

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Attention-Guided Second-Order Pooling Convolutional Networks

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Shannan Chen Qiule Sun Cunhua Li Jianxin Zhang Qiang Zhang Key Lab of Advanced Design and Intelligent Computing Dalian University China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology China School of Computer Engineering Jiangsu Ocean University China School of Computer Science and Engineering Dalian Minzu University China

Recently, channel attention-guided convolutional networks (ConvNets) have shown great advance on visual recognition tasks. However, they mainly exploit coarse first-order statistics to characterize holistic image and rarely focus on long-range feature dependencies, which limits the representation power in a certain. To handle above limitations, this paper proposes a novel attention-guided second-order pooling convolutional network (ASP-Net). ASP-Net introduces bilinear pooling that captures pairwise feature interactions to model second-order statistics. Meanwhile, it explicitly collects long-range dependencies via non-local operations, thus providing a global view in lower layers. Then, the second-order statistics and non-local context features are fused to obtain the enhanced representation for predicting channel-wise attention map and scaling convolution features. Experiment results on three commonly used datasets illuminate that ASP-Net outperforms its counterparts and achieves competitive performance.

关键词： Convolutional codes Visualization Convolution Conferences Network architecture Acoustics Task analysis

Three-dimensional computation visualization for computer graphics rendering algorithms 96

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Three-dimensional computation visualization for computer gra...

Proceedings of the twenty-seventh SIGCSE technical symposium on computer science education

作者： David A. Goldman Richard R. Eckert Maxine S. Cohen Human Computer Interaction Lab. Computer Science Dept. Thomas J. Watson School of Engineering and Applied Science Binghamton University Binghamton New York Staff Programmer - User Centered Design Solutions Boca Raton Florida

ISBN: (纸本)9780897917575

Computation visualization or algorithm animation is becoming an increasingly popular and effective way of teaching, debugging, and analyzing algorithms. Over the past ten years, several algorithm animation systems have been produced. Proposed here is a new approach and framework for visualizing three-dimensional algorithms or computations. Implemented on a prototype algorithm animation system, this framework, termed the vector-guided view, produces insightful visualizations of three-dimensional computation by effectively solving the problems of 3D scene navigation. The creation of this framework was motivated by the desire to produce visualizations of an increasingly large and complex set of rendering algorithms now ubiquitous in the field of computer graphics. To show the potential of this framework, a dynamic visualization of a recursive ray-tracing program has been created. A brief summary of the algorithm animation system is presented.

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Data Quality Assessment of Substation Data in Bangladesh: Insights from Handwritten Data Digitization

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Data Quality Assessment of Substation Data in Bangladesh: In...

International Conference on Power Systems (ICPS)

作者： Murshed Al Amin MD. Jawad-Al-Mursalin Hoque Zakia Nazzum Md Abu Sayed Sarker Tanveer Ahmed Rumee Moinul Islam Zaber Data and Design Lab Dhaka Bangladesh Military Institute of Science and Technology Independent University Bangladesh Department of Computer Science & Engineering University of Dhaka Dhaka Bangladesh United Nations University Guimarães Portugal

The assessment of power quality is vital for evaluating the existing state of the electricity supply, pinpointing its deficiencies, and guiding enhancements to guarantee a stable and consistent power supply, particularly in the face of rising demands from both industrial and residential sectors. In the context of Bangladesh, however, most substation data are still recorded manually, despite ongoing digitization efforts. This paper focuses on the quality of digitized transcription of handwritten substation data to determine its suitability for further analytical use. Our analysis revealed that the paper-based data from the substations exhibited significant gaps, undermining its reliability and accuracy. Through comprehensive evaluation, we concluded that the data, in its current state, is inadequate for in-depth analysis without the application of robust imputation methods. By tackling these challenges, our research aims to contribute to more informed decision-making and the efficient management of Bangladesh’s electrical infrastructure. This study not only diagnoses the current shortcomings in data quality but also lays the groundwork for future improvements in the country’s approach to energy data management.

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A General protocol for Distributed Quantum Gates

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arXiv 2018年

作者： Sarvaghad-Moghaddam, Moein Zomorodi-Moghadam, Mariam Farouk, Ahmed Quantum Design Automation Lab Amirkabir University of Technology Tehran 1 Iran Department of Computer Engineering Ferdowsi University of Mashhad Mashhad Iran Department of Physics and Computer Science Wilfrid Laurier University Waterloo Canada

Distributed quantum computation requires to apply quantum remote gates on separate nodes or subsystems of network. On the other hand, Toffoli gate is a universal and well-known quantum gate. It is frequently used in synthesis of quantum circuits. In this paper, a general protocol for implementing a remote η-qubit controlled-U gate is presented with minimum required resources. Then, the proposed method is applied for implementing a Toffoli gate in bipartite and tripartite systems. This method also is optimal when group of the qubits belong to one part, section or subsystem of network. Beucase it only use one entangled qubit for each group of the qubits in mentioned conditions. Copyright © 2018, The Authors. All rights reserved.

关键词： Qubits

Beyond Numbers: Creating Analogies to Enhance Data Comprehension and Communication with Generative AI

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arXiv 2024年

作者： Chen, Qing Shuai, Wei Zhang, Jiyao Sun, Zhida Cao, Nan Intelligent Big Data Visualization Lab Tongji University China College of Computer Science & Software Engineering Shenzhen University China Intelligent Big Data Visualization Lab Tongji College of Design and Innovation China

Unfamiliar measurements usually hinder readers from grasping the scale of the numerical data, understanding the content, and feeling engaged with the context. To enhance data comprehension and communication, we leverage analogies to bridge the gap between abstract data and familiar measurements. In this work, we first conduct semi-structured interviews with design experts to identify design problems and summarize design considerations. Then, we collect an analogy dataset of 138 cases from various online sources. Based on the collected dataset, we characterize a design space for creating data analogies. Next, we build a prototype system, AnalogyMate, that automatically suggests data analogies, their corresponding design solutions, and generated visual representations powered by generative AI. The study results show the usefulness of AnalogyMate in aiding the creation process of data analogies and the effectiveness of data analogy in enhancing data comprehension and communication. © 2024, CC BY.

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